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latent variable structural equation model

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Maximum Likelihood Estimation of Latent Variable Structural Equation Models: A Neural Network Approach

Saremi, Mehrzad

arXiv.org Machine LearningOct-5-2023

We propose a graphical structure for structural equation models that is stable under marginalization under linearity and Gaussianity assumptions. We show that computing the maximum likelihood estimation of this model is equivalent to training a neural network. We implement a GPU-based algorithm that computes the maximum likelihood estimation of these models.

artificial intelligence, latent variable structural equation model, machine learning, (3 more...)

arXiv.org Machine Learning

2309.14073

Genre: Research Report (0.69)

Technology:

Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (1.00)
Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Directed Networks > Bayesian Learning (1.00)

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